It is estimated that there are over 2 million manual wheelchair users in the United States. Up to 70% of manual wheelchair users report upper limb pain, which is mainly manifested in the shoulder and wrist. Shoulder pain in wheelchair users is linked to difficulty performing activities of daily living, decreased physical activity and decreased quality of life.
The main focus of this dissertation is to identify biomarkers from wheelchair propulsion data that are potentially related to shoulder pain in manual wheelchair users. Three biomarkers that distinguish between manual wheelchair users with and without shoulder pain are identified. The acceptability of the identified biomarkers are subjected to hypothesis testing using data collected from a sample of 30 experienced adult manual wheelchair users with and without shoulder pain. The results and their implications will be discussed. In this dissertation we will also discuss the interpretation and the physical significance of each of the results, a summary of limitations for the approaches adopted, and suggestions on the future course of research to address these limitations.
While the past two decades of research on shoulder pain and wheelchair propulsion has led to the development of important clinical guidelines, it has failed to identify specific biomarkers that may be related to shoulder pain in manual wheelchair users. This could be in part due to employing a binary approach by focusing on just (1) the pure bio-mechanical aspects, and (2) wheelchair design aspects (ergonomics). The originality of this dissertation is in the adoption of a multidisciplinary approach. Methodologies integrating theories and analyses from fields related to human movement science such as human motor control theory, non-linear dynamics and human factors (occupational ergonomics) are adopted to identify potential biomarkers that relate to shoulder pain in manual wheelchair users.
This dissertation concludes with preliminary results from a prototype wearable device, custom developed for manual wheelchair users. Wheelchair propulsion data obtained from the device will be benchmarked with data from the currently available technologies for tracking manual wheelchair propulsion (SMARTWheel and motion capture). This dissertation also proposes a framework for incorporating the research findings into the custom developed wearable technology for home-based rehabilitation training purposes.